In this subsection, we consider small world networks which are more realistically simulated neuronal networks [1]}. For simplicity, we focus on situations where \(TD\lesssim 0\)  for all neurons; this usually occurs when the initial potentials of primary neurons are far away from initial potentials of other neurons. We start networks with small number of neurons first. Fig. REF (a1,b1) show two examples of small world networks with 7 and 9 neurons respectively (referred as cases 7-8). These small world networks are constructed from regular networks model with 4 nearest neighbors and each connection is rewired with probability \(0.5\) . Similar to cases in regular network, we construct spiking propagation graphs (shown in Fig. REF (a3,b3)), based on neuronal initial potentials (listed in Table. REF ), neuronal network, and their spiking time difference \(TD\)  compared to situations in uncoupled networks. As expected, primary neurons first spike in the inter-bursts and propagate to secondary, and then tertiary neurons.
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